The present invention relates generally to the field of computer network management and in particular to a method of automatically monitoring critical network nodes via a self-terminating monitor application.
The ever-increasing capacity and throughput of computer networking technology has resulted in deployed computer networks of vast size and complexity. As the size and complexity of networks continues to grow, monitoring the health and status of network components and efficiently managing network resources becomes increasingly difficult. One known method of network monitoring and management deploys a “monitor” to some or all network or computing resources in the network, referred to herein as network “nodes.” This conventional monitor is an autonomous application that monitors the node's status and performance, and transmits event, status, and/or diagnostic information to one or more monitoring applications. A single monitoring application may monitor and control a subnet or other logical subset of network nodes, or alternatively may monitor and control the entire network.
Particularly in large networks, the amount of diagnostic and monitoring traffic generated between a monitoring application and a plurality of monitors may be significant. In addition to consuming network resources (i.e., bandwidth), heavy diagnostic traffic tends to drown critical “signal” in routine, non-critical “noise.” That is, important event and status information from network resources experiencing overloaded conditions, partial or total failures, or the like, may be difficult to extract from a large stream of routine, perfunctory status information and usage statistics continuously reported by conventional monitors running on healthy network nodes.
In addition, the type and granularity of information reported by conventional network monitors, while sufficient for routine maintenance tasks such as load balancing, is often insufficient to diagnose failures or other criticalities within the network. Thus, even when system management personnel are able to identify critical resource monitor reports, the reports often contain insufficient information to allow thorough diagnostics and troubleshooting.